As communications technologies rapidly develop, a scale of a communications network continuously enlarges and a structure of the communications network becomes more complex. The communications network is formed by interconnection of a large quantity of devices and links. When a certain device or link is faulty, an alarm is generated. In addition, because the device or the link may be associated with multiple devices or links, when the device or the link is faulty, a device or a link that is associated with the device or link may become faulty and generate an alarm, where the alarm generated by the faulty device or link is a cause alarm, and the alarm generated by the device or link that is associated with the device or the link is a correlative alarm. When alarms are generated in the communications network, correlation analysis on the generated alarms is required to analyze the cause alarm and the correlative alarm from the generated alarms, so that operation and maintenance personnel process the cause alarm, thereby ensuring normal running of the communications network. Automatically identifying the cause alarm by using a function of correlation analysis so that the operation and maintenance personnel process the cause alarm has become an important means for quick troubleshooting, which greatly improves the troubleshooting efficiency of the operation and maintenance personnel. At present, the function of correlation analysis still adopts single-engine analysis, and an existing processing mechanism has the following problems: an efficiency bottleneck exists, and a single engine has an efficiency upper limit, failing to meet an increasingly high requirement; and multi-core resources cannot be fully utilized to exert an advantage of parallel processing.